What the data for this category looks like
The data for this category comes from raw and auxiliary material qualification certificates, ERP/MES systems, weighing equipment, ovens or frying lines, laboratory testing equipment, and food traceability ledgers. Daily documents include formulas and feeding lists, production records, baking or steaming curves, metal detection records, cleaning and disinfection records, and factory inspection reports. Data update frequency is per batch, per shift, or daily. Document fields include feeding quantity, baking temperature and duration, allergen labeling, packaging date, shelf life, and more. Some documents are updated frequently when product lines are switched.
What constraints these characteristics impose on the deployment and upgrade phase
The characteristics of frequent product line switches and multi-batch data updates for this category require that the deployment phase supports quick access to new category documents and incremental synchronization configurations. The multi-type, multi-field document structure requires matching storage and index configurations that support multi-source heterogeneous data. The high compliance requirements for allergen control and cleaning and disinfection records mean that the upgrade phase must reserve extended interfaces for compliance verification. The ready-to-eat product attribute requires that the post-deployment verification phase covers full-link verification of core business documents, to avoid data anomalies caused by configuration oversights.
How to configure the settings
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://[factory account]:[factory password]@[internal database address]:27017/fastgpt?authSource=admin | This category’s multi-type unstructured documents require adaptable storage. Standard port and authentication configurations ensure secure access to production data, and are compatible with FastGPT v4.17.0 multi-source document storage logic |
REDIS_URL | redis://:[cache password]@[internal cache address]:6379/0 | Frequently updated production documents require cached index results. Standard port configuration ensures cache response speed |
STORAGE_S3_ENDPOINT | http://[internal object storage address]:9000 | Multi-batch production documents require unified bulk storage. Standard object storage port is compatible with the factory’s existing storage architecture |
DB_MAX_LINK | 80–150 connections | Multi-source system synchronization requires controlling database connection counts to avoid excessive resource usage that disrupts production system operations |
FE_DOMAIN | https://[baked goods factory internal business domain] | Binding the business domain ensures internal access permissions, and avoids access anomalies caused by cross-domain configuration issues |
FILE_TOKEN_KEY | [32-bit custom random string] | Protects the security of tokens for document upload and download, and is compatible with the factory’s internal permission control rules |
Three common configuration mistakes
- Symptom: Accessing the deployed service page returns 405 Method Not Allowed, and technical documents fail to load. Cause: The cross-domain access rules for
STORAGE_S3_ENDPOINTare not configured correctly, or the frontend domainFE_DOMAINis not added to the backend service’s allowed access list. - Symptom: Production records and formula documents fail to sync after startup, with a database connection failure prompt. Cause: The
authSource=adminauthentication parameter is not added toMONGODB_URI, or database access permissions are not granted to the deployment node’s IP address. - Symptom: Exclusive document review permissions cannot be assigned to different production lines, and team management functions do not work. Cause: The permission scope of
ROOT_KEYis not configured correctly, orFE_DOMAINis not bound to the internal permission control system.
How to confirm the configuration is complete
- Log in to the database corresponding to
MONGODB_URI, check if FastGPT-related document collections exist, and confirm that indexes for production documents have been successfully created. - Access the frontend address bound to
FE_DOMAIN, attempt to upload a test cleaning and disinfection record, and confirm that the file can be stored and read normally. - Run a database connection count test, confirm that the connection count meets business requirements, and that no connection overflow errors occur.
- Attempt to create a document review task for a test production line, confirm that the permission configuration works normally, and that no permission interception prompts appear.
The values provided are common starting points, and should be evaluated against the reader’s own samples.